@article{ZHANG2023, 
author = {Jinlong ZHANG and Yan YANG},
title = {Single image dehazing based on hazy features extraction and enhancement network},
year = {2023},
journal = {Journal of Measurement Science and Instrumentation},
volume = {14},
number = {1},
pages = {45-54},
keywords = {image dehazing, hazy features extraction, texture restoration, enhancement network, adaptive residual, channel attention},
url = {https://www.sciopen.com/article/10.62756/jmsi.1674-8042.2023006},
doi = {10.62756/jmsi.1674-8042.2023006},
abstract = {Convolutional neural network is developing rapidly in image processing. Most image dehazing algorithms only focus on dehazing but neglect the overall quality of dehazing image, which leads to problems such as loss of information blurred texture, etc. To solve these problems, we propose a dehazing and enhancement convolutional neural network. Hazy image and clear image are obtained by encoding and decoding. Enhancement network is used to restore the texture and details of dehazing image. Experiments show that the proposed method has excellent results in subjective evaluation and quality indexes. Haze can be removed more thoroughly, and images with clearer details and texture can be obtained.}
}